Type 2 Diabetes (T2D) is a serious health concern. Identifying and understanding gene expression patterns associated with the disease can help uncover underlying biological mechanisms and could potentially support earlier detection.
Our analysis is focused on:
Identifying gene expression markers
Identifying key over- and under-expressed genes
Looking into co-expression of key genes
Data source:
“A Systems Genetics Approach Identifies Genes and Pathways for Type 2 Diabetes in Human Islets” (PMID: 22768844) (GEO ID: GDS4337)
Data set overview:
14481 different genes
63 pancreatic islets samples
9 with T2D
54 controls
Descriptive statistics:
Similar mean gene expression across groups
Overall low mean expression levels
Slightly right-skewed distribution
=> Testing for significant differential expression between the two groups

Frederik
Goal: Identify genes with largest expression differences between T2D and control
Workflow:
Compute median expression per gene for T2D and Control
Calculate absolute differences between group medians per gene
Rank genes by largest absolute difference
Visualize top genes:
Bolette
Per gene:
T2D: 9 samples
Control: 54 samples
Final p-value selection was p < 0.01
635 genes labelled significant
Top 30 most significant (lowest p-vals) chosen for visualisation

vælger 10 gener, correlation matrix
Bolette
1) Difference in two methods
2) Sum up which genes are found by the analysis
3) does they support the litterature? uniprot…